Digital twin driven prognostics and health management for complex equipment

被引：508
|
作者：
Tao, Fei [1 ]
Zhang, Meng [1 ]
Liu, Yushan [1 ]
Nee, A. Y. C. [2 ]
机构：
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Natl Univ Singapore, Dept Mech Engn, Singapore 117576, Singapore
来源：
CIRP ANNALS-MANUFACTURING TECHNOLOGY | 2018年 / 67卷 / 01期
关键词：
Maintenance; Condition monitoring; Digital twin;
D O I：
10.1016/j.cirp.2018.04.055
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Prognostics and health management (PHM) is crucial in the lifecycle monitoring of a product, especially for complex equipment working in a harsh environment. In order to improve the accuracy and efficiency of PHM, digital twin (DT), an emerging technology to achieve physical-virtual convergence, is proposed for complex equipment. A general DT for complex equipment is first constructed, then a new method using DT driven PHM is proposed, making effective use of the interaction mechanism and fused data of DT. A case study of a wind turbine is used to illustrate the effectiveness of the proposed method. (C) 2018 Published by Elsevier Ltd on behalf of CIRP.
引用
收藏
页码：169 / 172
页数：4
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